mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-12-12 12:06:04 +00:00
Allow markdown and python files to be referenced direclty and add it to
the docs Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo
parent
7ab63068f8
commit
9ccd2e4e9b
11 changed files with 493 additions and 1145 deletions
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@ -15,16 +15,39 @@ You can open up the docs in your browser at http://localhost:3000
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## File Import System
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This documentation uses a custom component to import files directly from the repository, eliminating copy-paste maintenance:
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This documentation uses `remark-code-import` to import files directly from the repository, eliminating copy-paste maintenance. Files are automatically embedded during build time.
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```jsx
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import CodeFromFile from '@site/src/components/CodeFromFile';
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### Importing Code Files
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<CodeFromFile src="path/to/file.py" />
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<CodeFromFile src="README.md" startLine={1} endLine={20} />
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To import Python code (or any code files) with syntax highlighting, use this syntax in `.mdx` files:
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```markdown
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```python file=./demo_script.py title="demo_script.py"
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```
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```
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Files are automatically synced from the repo root when building. See the `CodeFromFile` component for syntax highlighting, line ranges, and multi-language support.
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This automatically imports the file content and displays it as a formatted code block with Python syntax highlighting.
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**Note:** Paths are relative to the current `.mdx` file location, not the repository root.
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### Importing Markdown Files as Content
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For importing and rendering markdown files (like CONTRIBUTING.md), use the raw-loader approach:
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```jsx
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import Contributing from '!!raw-loader!../../../CONTRIBUTING.md';
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import ReactMarkdown from 'react-markdown';
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<ReactMarkdown>{Contributing}</ReactMarkdown>
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```
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**Requirements:**
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- Install dependencies: `npm install --save-dev raw-loader react-markdown`
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**Path Resolution:**
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- For `remark-code-import`: Paths are relative to the current `.mdx` file location
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- For `raw-loader`: Paths are relative to the current `.mdx` file location
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- Use `../` to navigate up directories as needed
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## Content
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@ -1,232 +1,13 @@
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# Contributing to Llama Stack
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We want to make contributing to this project as easy and transparent as
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possible.
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---
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title: Contributing
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description: Contributing to Llama Stack
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sidebar_label: Contributing to Llama Stack
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sidebar_position: 3
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hide_title: true
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---
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## Set up your development environment
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import Contributing from '!!raw-loader!../../../CONTRIBUTING.md';
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import ReactMarkdown from 'react-markdown';
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We use [uv](https://github.com/astral-sh/uv) to manage python dependencies and virtual environments.
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You can install `uv` by following this [guide](https://docs.astral.sh/uv/getting-started/installation/).
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You can install the dependencies by running:
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```bash
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cd llama-stack
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uv sync --group dev
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uv pip install -e .
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source .venv/bin/activate
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```
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```{note}
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You can use a specific version of Python with `uv` by adding the `--python <version>` flag (e.g. `--python 3.12`).
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Otherwise, `uv` will automatically select a Python version according to the `requires-python` section of the `pyproject.toml`.
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For more info, see the [uv docs around Python versions](https://docs.astral.sh/uv/concepts/python-versions/).
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```
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Note that you can create a dotenv file `.env` that includes necessary environment variables:
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```
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LLAMA_STACK_BASE_URL=http://localhost:8321
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LLAMA_STACK_CLIENT_LOG=debug
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LLAMA_STACK_PORT=8321
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LLAMA_STACK_CONFIG=<provider-name>
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TAVILY_SEARCH_API_KEY=
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BRAVE_SEARCH_API_KEY=
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```
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And then use this dotenv file when running client SDK tests via the following:
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```bash
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uv run --env-file .env -- pytest -v tests/integration/inference/test_text_inference.py --text-model=meta-llama/Llama-3.1-8B-Instruct
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```
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### Pre-commit Hooks
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We use [pre-commit](https://pre-commit.com/) to run linting and formatting checks on your code. You can install the pre-commit hooks by running:
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```bash
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uv run pre-commit install
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```
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After that, pre-commit hooks will run automatically before each commit.
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Alternatively, if you don't want to install the pre-commit hooks, you can run the checks manually by running:
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```bash
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uv run pre-commit run --all-files
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```
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```{caution}
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Before pushing your changes, make sure that the pre-commit hooks have passed successfully.
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```
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## Discussions -> Issues -> Pull Requests
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We actively welcome your pull requests. However, please read the following. This is heavily inspired by [Ghostty](https://github.com/ghostty-org/ghostty/blob/main/CONTRIBUTING.md).
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If in doubt, please open a [discussion](https://github.com/meta-llama/llama-stack/discussions); we can always convert that to an issue later.
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### Issues
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We use GitHub issues to track public bugs. Please ensure your description is
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clear and has sufficient instructions to be able to reproduce the issue.
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Meta has a [bounty program](http://facebook.com/whitehat/info) for the safe
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disclosure of security bugs. In those cases, please go through the process
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outlined on that page and do not file a public issue.
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|
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### Contributor License Agreement ("CLA")
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In order to accept your pull request, we need you to submit a CLA. You only need
|
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to do this once to work on any of Meta's open source projects.
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Complete your CLA here: [https://code.facebook.com/cla](https://code.facebook.com/cla)
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**I'd like to contribute!**
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If you are new to the project, start by looking at the issues tagged with "good first issue". If you're interested
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leave a comment on the issue and a triager will assign it to you.
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Please avoid picking up too many issues at once. This helps you stay focused and ensures that others in the community also have opportunities to contribute.
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- Try to work on only 1–2 issues at a time, especially if you’re still getting familiar with the codebase.
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- Before taking an issue, check if it’s already assigned or being actively discussed.
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- If you’re blocked or can’t continue with an issue, feel free to unassign yourself or leave a comment so others can step in.
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**I have a bug!**
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1. Search the issue tracker and discussions for similar issues.
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2. If you don't have steps to reproduce, open a discussion.
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3. If you have steps to reproduce, open an issue.
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**I have an idea for a feature!**
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1. Open a discussion.
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**I've implemented a feature!**
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1. If there is an issue for the feature, open a pull request.
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2. If there is no issue, open a discussion and link to your branch.
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**I have a question!**
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1. Open a discussion or use [Discord](https://discord.gg/llama-stack).
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**Opening a Pull Request**
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1. Fork the repo and create your branch from `main`.
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2. If you've changed APIs, update the documentation.
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3. Ensure the test suite passes.
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4. Make sure your code lints using `pre-commit`.
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5. If you haven't already, complete the Contributor License Agreement ("CLA").
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6. Ensure your pull request follows the [conventional commits format](https://www.conventionalcommits.org/en/v1.0.0/).
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7. Ensure your pull request follows the [coding style](#coding-style).
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Please keep pull requests (PRs) small and focused. If you have a large set of changes, consider splitting them into logically grouped, smaller PRs to facilitate review and testing.
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```{tip}
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As a general guideline:
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- Experienced contributors should try to keep no more than 5 open PRs at a time.
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- New contributors are encouraged to have only one open PR at a time until they’re familiar with the codebase and process.
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```
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## Repository guidelines
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### Coding Style
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* Comments should provide meaningful insights into the code. Avoid filler comments that simply
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describe the next step, as they create unnecessary clutter, same goes for docstrings.
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* Prefer comments to clarify surprising behavior and/or relationships between parts of the code
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rather than explain what the next line of code does.
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* Catching exceptions, prefer using a specific exception type rather than a broad catch-all like
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`Exception`.
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* Error messages should be prefixed with "Failed to ..."
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* 4 spaces for indentation rather than tab
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* When using `# noqa` to suppress a style or linter warning, include a comment explaining the
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justification for bypassing the check.
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* When using `# type: ignore` to suppress a mypy warning, include a comment explaining the
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justification for bypassing the check.
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* Don't use unicode characters in the codebase. ASCII-only is preferred for compatibility or
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readability reasons.
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* Providers configuration class should be Pydantic Field class. It should have a `description` field
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that describes the configuration. These descriptions will be used to generate the provider
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documentation.
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* When possible, use keyword arguments only when calling functions.
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* Llama Stack utilizes custom Exception classes for certain Resources that should be used where applicable.
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### License
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By contributing to Llama, you agree that your contributions will be licensed
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under the LICENSE file in the root directory of this source tree.
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## Common Tasks
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Some tips about common tasks you work on while contributing to Llama Stack:
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### Setup for development
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```bash
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git clone https://github.com/meta-llama/llama-stack.git
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cd llama-stack
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uv run llama stack list-deps <distro-name> | xargs -L1 uv pip install
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# (Optional) If you are developing the llama-stack-client-python package, you can add it as an editable package.
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git clone https://github.com/meta-llama/llama-stack-client-python.git
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uv add --editable ../llama-stack-client-python
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```
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### Updating distribution configurations
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If you have made changes to a provider's configuration in any form (introducing a new config key, or
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changing models, etc.), you should run `./scripts/distro_codegen.py` to re-generate various YAML
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files as well as the documentation. You should not change `docs/source/.../distributions/` files
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manually as they are auto-generated.
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### Updating the provider documentation
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If you have made changes to a provider's configuration, you should run `./scripts/provider_codegen.py`
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to re-generate the documentation. You should not change `docs/source/.../providers/` files manually
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as they are auto-generated.
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Note that the provider "description" field will be used to generate the provider documentation.
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### Building the Documentation
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If you are making changes to the documentation at [https://llamastack.github.io/](https://llamastack.github.io/), you can use the following command to build the documentation and preview your changes.
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```bash
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# This rebuilds the documentation pages and the OpenAPI spec.
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npm install
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npm run gen-api-docs all
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npm run build
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# This will start a local server (usually at http://127.0.0.1:3000).
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npm run serve
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```
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### Update API Documentation
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If you modify or add new API endpoints, update the API documentation accordingly. You can do this by running the following command:
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```bash
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uv run ./docs/openapi_generator/run_openapi_generator.sh
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```
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The generated API schema will be available in `docs/static/`. Make sure to review the changes before committing.
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## Adding a New Provider
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See:
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- [Adding a New API Provider Page](./new_api_provider.mdx) which describes how to add new API providers to the Stack.
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- [Vector Database Page](./new_vector_database.mdx) which describes how to add a new vector databases with Llama Stack.
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- [External Provider Page](/docs/providers/external/) which describes how to add external providers to the Stack.
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## Testing
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See the [Testing README](https://github.com/meta-llama/llama-stack/blob/main/tests/README.md) for detailed testing information.
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## Advanced Topics
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For developers who need deeper understanding of the testing system internals:
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- [Record-Replay Testing](./testing/record-replay.mdx)
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### Benchmarking
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See the [Benchmarking README](https://github.com/meta-llama/llama-stack/blob/main/benchmarking/k8s-benchmark/README.md) for benchmarking information.
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<ReactMarkdown>{Contributing}</ReactMarkdown>
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|
|
|
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|
|
@ -24,6 +24,9 @@ ollama run llama3.2:3b --keepalive 60m
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#### Step 2: Run the Llama Stack server
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```python file=./demo_script.py title="demo_script.py"
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```
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We will use `uv` to install dependencies and run the Llama Stack server.
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```bash
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# Install dependencies for the starter distribution
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@ -35,9 +38,6 @@ OLLAMA_URL=http://localhost:11434 uv run --with llama-stack llama stack run star
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#### Step 3: Run the demo
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Now open up a new terminal and copy the following script into a file named `demo_script.py`.
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import CodeFromFile from '@site/src/components/CodeFromFile';
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<CodeFromFile src="demo_script.py" title="demo_script.py" />
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We will use `uv` to run the script
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```
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uv run --with llama-stack-client,fire,requests demo_script.py
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|
|
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@ -71,6 +71,11 @@ const config: Config = {
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docs: {
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sidebarPath: require.resolve("./sidebars.ts"),
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docItemComponent: "@theme/ApiItem", // Derived from docusaurus-theme-openapi
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remarkPlugins: [
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[require('remark-code-import'), {
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rootDir: require('path').join(__dirname, '..') // Repository root
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}]
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],
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},
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blog: false,
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theme: {
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|
|
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1044
docs/package-lock.json
generated
1044
docs/package-lock.json
generated
File diff suppressed because it is too large
Load diff
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@ -4,8 +4,8 @@
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"private": true,
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"scripts": {
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"docusaurus": "docusaurus",
|
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"start": "npm run sync-files && docusaurus start",
|
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"build": "npm run sync-files && docusaurus build",
|
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"start": "docusaurus start",
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"build": "docusaurus build",
|
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"swizzle": "docusaurus swizzle",
|
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"deploy": "docusaurus deploy",
|
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"clear": "docusaurus clear",
|
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|
|
@ -28,7 +28,8 @@
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"docusaurus-theme-openapi-docs": "4.3.7",
|
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"prism-react-renderer": "^2.3.0",
|
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"react": "^19.0.0",
|
||||
"react-dom": "^19.0.0"
|
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"react-dom": "^19.0.0",
|
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"remark-code-import": "^1.2.0"
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},
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"browserslist": {
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"production": [
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|
|
@ -41,5 +42,9 @@
|
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"last 1 firefox version",
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"last 1 safari version"
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]
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},
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"devDependencies": {
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"raw-loader": "^4.0.2",
|
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"react-markdown": "^10.1.0"
|
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}
|
||||
}
|
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|
|
|
|||
|
|
@ -47,6 +47,57 @@ function trackFileUsage(filePath) {
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|||
}
|
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}
|
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|
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// Filter content based on file type and options
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function filterContent(content, filePath) {
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let lines = content.split('\n');
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|
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// Skip copyright header for Python files
|
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if (filePath.endsWith('.py')) {
|
||||
// Read the license header file
|
||||
const licenseHeaderPath = path.join(repoRoot, 'docs', 'license_header.txt');
|
||||
if (fs.existsSync(licenseHeaderPath)) {
|
||||
try {
|
||||
const licenseText = fs.readFileSync(licenseHeaderPath, 'utf8');
|
||||
const licenseLines = licenseText.trim().split('\n');
|
||||
|
||||
// Check if file starts with the license header (accounting for # comments)
|
||||
if (lines.length >= licenseLines.length) {
|
||||
let matches = true;
|
||||
for (let i = 0; i < licenseLines.length; i++) {
|
||||
const codeLine = lines[i]?.replace(/^#\s*/, '').trim();
|
||||
const licenseLine = licenseLines[i]?.trim();
|
||||
if (codeLine !== licenseLine) {
|
||||
matches = false;
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||||
break;
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||||
}
|
||||
}
|
||||
|
||||
if (matches) {
|
||||
// Skip the license header and any trailing empty lines
|
||||
let skipTo = licenseLines.length;
|
||||
while (skipTo < lines.length && lines[skipTo].trim() === '') {
|
||||
skipTo++;
|
||||
}
|
||||
lines = lines.slice(skipTo);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.warn(`Could not read license header, skipping filtering for ${filePath}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Trim empty lines from start and end
|
||||
while (lines.length > 0 && lines[0].trim() === '') {
|
||||
lines.shift();
|
||||
}
|
||||
while (lines.length > 0 && lines[lines.length - 1].trim() === '') {
|
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lines.pop();
|
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}
|
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|
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return lines.join('\n');
|
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}
|
||||
|
||||
// Sync a file from repo root to static directory
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function syncFile(filePath) {
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const sourcePath = path.join(repoRoot, filePath);
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||||
|
|
@ -61,7 +112,8 @@ function syncFile(filePath) {
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|||
try {
|
||||
if (fs.existsSync(sourcePath)) {
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const content = fs.readFileSync(sourcePath, 'utf8');
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fs.writeFileSync(destPath, content);
|
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const filteredContent = filterContent(content, filePath);
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fs.writeFileSync(destPath, filteredContent);
|
||||
console.log(`✅ Synced ${filePath}`);
|
||||
trackFileUsage(filePath);
|
||||
return true;
|
||||
|
|
|
|||
|
|
@ -15,33 +15,7 @@ export default function CodeFromFile({
|
|||
useEffect(() => {
|
||||
async function loadFile() {
|
||||
try {
|
||||
// Register this file for syncing (build-time only)
|
||||
if (typeof window === 'undefined') {
|
||||
// This runs during build - register the file
|
||||
const fs = require('fs');
|
||||
const path = require('path');
|
||||
|
||||
const usageFile = path.join(process.cwd(), 'static', 'imported-files', 'usage.json');
|
||||
const usageDir = path.dirname(usageFile);
|
||||
|
||||
if (!fs.existsSync(usageDir)) {
|
||||
fs.mkdirSync(usageDir, { recursive: true });
|
||||
}
|
||||
|
||||
let usage = { files: [] };
|
||||
if (fs.existsSync(usageFile)) {
|
||||
try {
|
||||
usage = JSON.parse(fs.readFileSync(usageFile, 'utf8'));
|
||||
} catch (error) {
|
||||
console.warn('Could not read existing usage file');
|
||||
}
|
||||
}
|
||||
|
||||
if (!usage.files.includes(src)) {
|
||||
usage.files.push(src);
|
||||
fs.writeFileSync(usageFile, JSON.stringify(usage, null, 2));
|
||||
}
|
||||
}
|
||||
// File registration is now handled by the file-sync-plugin during build
|
||||
|
||||
// Load file from static/imported-files directory
|
||||
const response = await fetch(`/imported-files/${src}`);
|
||||
|
|
@ -50,7 +24,7 @@ export default function CodeFromFile({
|
|||
}
|
||||
let text = await response.text();
|
||||
|
||||
// Handle line range if specified
|
||||
// Handle line range if specified (filtering is done at build time)
|
||||
if (startLine || endLine) {
|
||||
const lines = text.split('\n');
|
||||
const start = startLine ? Math.max(0, startLine - 1) : 0;
|
||||
|
|
|
|||
207
docs/static/imported-files/README.md
vendored
207
docs/static/imported-files/README.md
vendored
|
|
@ -1,207 +0,0 @@
|
|||
# Llama Stack
|
||||
|
||||
[](https://pypi.org/project/llama_stack/)
|
||||
[](https://pypi.org/project/llama-stack/)
|
||||
[](https://github.com/meta-llama/llama-stack/blob/main/LICENSE)
|
||||
[](https://discord.gg/llama-stack)
|
||||
[](https://github.com/meta-llama/llama-stack/actions/workflows/unit-tests.yml?query=branch%3Amain)
|
||||
[](https://github.com/meta-llama/llama-stack/actions/workflows/integration-tests.yml?query=branch%3Amain)
|
||||
|
||||
[**Quick Start**](https://llamastack.github.io/docs/getting_started/quickstart) | [**Documentation**](https://llamastack.github.io/docs) | [**Colab Notebook**](./docs/getting_started.ipynb) | [**Discord**](https://discord.gg/llama-stack)
|
||||
|
||||
|
||||
### ✨🎉 Llama 4 Support 🎉✨
|
||||
We released [Version 0.2.0](https://github.com/meta-llama/llama-stack/releases/tag/v0.2.0) with support for the Llama 4 herd of models released by Meta.
|
||||
|
||||
<details>
|
||||
|
||||
<summary>👋 Click here to see how to run Llama 4 models on Llama Stack </summary>
|
||||
|
||||
\
|
||||
*Note you need 8xH100 GPU-host to run these models*
|
||||
|
||||
```bash
|
||||
pip install -U llama_stack
|
||||
|
||||
MODEL="Llama-4-Scout-17B-16E-Instruct"
|
||||
# get meta url from llama.com
|
||||
huggingface-cli download meta-llama/$MODEL --local-dir ~/.llama/$MODEL
|
||||
|
||||
# start a llama stack server
|
||||
INFERENCE_MODEL=meta-llama/$MODEL llama stack build --run --template meta-reference-gpu
|
||||
|
||||
# install client to interact with the server
|
||||
pip install llama-stack-client
|
||||
```
|
||||
### CLI
|
||||
```bash
|
||||
# Run a chat completion
|
||||
MODEL="Llama-4-Scout-17B-16E-Instruct"
|
||||
|
||||
llama-stack-client --endpoint http://localhost:8321 \
|
||||
inference chat-completion \
|
||||
--model-id meta-llama/$MODEL \
|
||||
--message "write a haiku for meta's llama 4 models"
|
||||
|
||||
OpenAIChatCompletion(
|
||||
...
|
||||
choices=[
|
||||
OpenAIChatCompletionChoice(
|
||||
finish_reason='stop',
|
||||
index=0,
|
||||
message=OpenAIChatCompletionChoiceMessageOpenAIAssistantMessageParam(
|
||||
role='assistant',
|
||||
content='...**Silent minds awaken,** \n**Whispers of billions of words,** \n**Reasoning breaks the night.** \n\n— \n*This haiku blends the essence of LLaMA 4\'s capabilities with nature-inspired metaphor, evoking its vast training data and transformative potential.*',
|
||||
...
|
||||
),
|
||||
...
|
||||
)
|
||||
],
|
||||
...
|
||||
)
|
||||
```
|
||||
### Python SDK
|
||||
```python
|
||||
from llama_stack_client import LlamaStackClient
|
||||
|
||||
client = LlamaStackClient(base_url=f"http://localhost:8321")
|
||||
|
||||
model_id = "meta-llama/Llama-4-Scout-17B-16E-Instruct"
|
||||
prompt = "Write a haiku about coding"
|
||||
|
||||
print(f"User> {prompt}")
|
||||
response = client.chat.completions.create(
|
||||
model=model_id,
|
||||
messages=[
|
||||
{"role": "system", "content": "You are a helpful assistant."},
|
||||
{"role": "user", "content": prompt},
|
||||
],
|
||||
)
|
||||
print(f"Assistant> {response.choices[0].message.content}")
|
||||
```
|
||||
As more providers start supporting Llama 4, you can use them in Llama Stack as well. We are adding to the list. Stay tuned!
|
||||
|
||||
|
||||
</details>
|
||||
|
||||
### 🚀 One-Line Installer 🚀
|
||||
|
||||
To try Llama Stack locally, run:
|
||||
|
||||
```bash
|
||||
curl -LsSf https://github.com/meta-llama/llama-stack/raw/main/scripts/install.sh | bash
|
||||
```
|
||||
|
||||
### Overview
|
||||
|
||||
Llama Stack standardizes the core building blocks that simplify AI application development. It codifies best practices across the Llama ecosystem. More specifically, it provides
|
||||
|
||||
- **Unified API layer** for Inference, RAG, Agents, Tools, Safety, Evals, and Telemetry.
|
||||
- **Plugin architecture** to support the rich ecosystem of different API implementations in various environments, including local development, on-premises, cloud, and mobile.
|
||||
- **Prepackaged verified distributions** which offer a one-stop solution for developers to get started quickly and reliably in any environment.
|
||||
- **Multiple developer interfaces** like CLI and SDKs for Python, Typescript, iOS, and Android.
|
||||
- **Standalone applications** as examples for how to build production-grade AI applications with Llama Stack.
|
||||
|
||||
<div style="text-align: center;">
|
||||
<img
|
||||
src="https://github.com/user-attachments/assets/33d9576d-95ea-468d-95e2-8fa233205a50"
|
||||
width="480"
|
||||
title="Llama Stack"
|
||||
alt="Llama Stack"
|
||||
/>
|
||||
</div>
|
||||
|
||||
### Llama Stack Benefits
|
||||
- **Flexible Options**: Developers can choose their preferred infrastructure without changing APIs and enjoy flexible deployment choices.
|
||||
- **Consistent Experience**: With its unified APIs, Llama Stack makes it easier to build, test, and deploy AI applications with consistent application behavior.
|
||||
- **Robust Ecosystem**: Llama Stack is already integrated with distribution partners (cloud providers, hardware vendors, and AI-focused companies) that offer tailored infrastructure, software, and services for deploying Llama models.
|
||||
|
||||
By reducing friction and complexity, Llama Stack empowers developers to focus on what they do best: building transformative generative AI applications.
|
||||
|
||||
### API Providers
|
||||
Here is a list of the various API providers and available distributions that can help developers get started easily with Llama Stack.
|
||||
Please checkout for [full list](https://llamastack.github.io/docs/providers)
|
||||
|
||||
| API Provider Builder | Environments | Agents | Inference | VectorIO | Safety | Telemetry | Post Training | Eval | DatasetIO |
|
||||
|:--------------------:|:------------:|:------:|:---------:|:--------:|:------:|:---------:|:-------------:|:----:|:--------:|
|
||||
| Meta Reference | Single Node | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
| SambaNova | Hosted | | ✅ | | ✅ | | | | |
|
||||
| Cerebras | Hosted | | ✅ | | | | | | |
|
||||
| Fireworks | Hosted | ✅ | ✅ | ✅ | | | | | |
|
||||
| AWS Bedrock | Hosted | | ✅ | | ✅ | | | | |
|
||||
| Together | Hosted | ✅ | ✅ | | ✅ | | | | |
|
||||
| Groq | Hosted | | ✅ | | | | | | |
|
||||
| Ollama | Single Node | | ✅ | | | | | | |
|
||||
| TGI | Hosted/Single Node | | ✅ | | | | | | |
|
||||
| NVIDIA NIM | Hosted/Single Node | | ✅ | | ✅ | | | | |
|
||||
| ChromaDB | Hosted/Single Node | | | ✅ | | | | | |
|
||||
| Milvus | Hosted/Single Node | | | ✅ | | | | | |
|
||||
| Qdrant | Hosted/Single Node | | | ✅ | | | | | |
|
||||
| Weaviate | Hosted/Single Node | | | ✅ | | | | | |
|
||||
| SQLite-vec | Single Node | | | ✅ | | | | | |
|
||||
| PG Vector | Single Node | | | ✅ | | | | | |
|
||||
| PyTorch ExecuTorch | On-device iOS | ✅ | ✅ | | | | | | |
|
||||
| vLLM | Single Node | | ✅ | | | | | | |
|
||||
| OpenAI | Hosted | | ✅ | | | | | | |
|
||||
| Anthropic | Hosted | | ✅ | | | | | | |
|
||||
| Gemini | Hosted | | ✅ | | | | | | |
|
||||
| WatsonX | Hosted | | ✅ | | | | | | |
|
||||
| HuggingFace | Single Node | | | | | | ✅ | | ✅ |
|
||||
| TorchTune | Single Node | | | | | | ✅ | | |
|
||||
| NVIDIA NEMO | Hosted | | ✅ | ✅ | | | ✅ | ✅ | ✅ |
|
||||
| NVIDIA | Hosted | | | | | | ✅ | ✅ | ✅ |
|
||||
|
||||
> **Note**: Additional providers are available through external packages. See [External Providers](https://llamastack.github.io/docs/providers/external) documentation.
|
||||
|
||||
### Distributions
|
||||
|
||||
A Llama Stack Distribution (or "distro") is a pre-configured bundle of provider implementations for each API component. Distributions make it easy to get started with a specific deployment scenario - you can begin with a local development setup (eg. ollama) and seamlessly transition to production (eg. Fireworks) without changing your application code.
|
||||
Here are some of the distributions we support:
|
||||
|
||||
| **Distribution** | **Llama Stack Docker** | Start This Distribution |
|
||||
|:---------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------:|
|
||||
| Starter Distribution | [llamastack/distribution-starter](https://hub.docker.com/repository/docker/llamastack/distribution-starter/general) | [Guide](https://llamastack.github.io/latest/distributions/self_hosted_distro/starter.html) |
|
||||
| Meta Reference | [llamastack/distribution-meta-reference-gpu](https://hub.docker.com/repository/docker/llamastack/distribution-meta-reference-gpu/general) | [Guide](https://llamastack.github.io/latest/distributions/self_hosted_distro/meta-reference-gpu.html) |
|
||||
| PostgreSQL | [llamastack/distribution-postgres-demo](https://hub.docker.com/repository/docker/llamastack/distribution-postgres-demo/general) | |
|
||||
|
||||
### Documentation
|
||||
|
||||
Please checkout our [Documentation](https://llamastack.github.io/latest/index.html) page for more details.
|
||||
|
||||
* CLI references
|
||||
* [llama (server-side) CLI Reference](https://llamastack.github.io/latest/references/llama_cli_reference/index.html): Guide for using the `llama` CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.
|
||||
* [llama (client-side) CLI Reference](https://llamastack.github.io/latest/references/llama_stack_client_cli_reference.html): Guide for using the `llama-stack-client` CLI, which allows you to query information about the distribution.
|
||||
* Getting Started
|
||||
* [Quick guide to start a Llama Stack server](https://llamastack.github.io/latest/getting_started/index.html).
|
||||
* [Jupyter notebook](./docs/getting_started.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
|
||||
* The complete Llama Stack lesson [Colab notebook](https://colab.research.google.com/drive/1dtVmxotBsI4cGZQNsJRYPrLiDeT0Wnwt) of the new [Llama 3.2 course on Deeplearning.ai](https://learn.deeplearning.ai/courses/introducing-multimodal-llama-3-2/lesson/8/llama-stack).
|
||||
* A [Zero-to-Hero Guide](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide) that guide you through all the key components of llama stack with code samples.
|
||||
* [Contributing](CONTRIBUTING.md)
|
||||
* [Adding a new API Provider](https://llamastack.github.io/latest/contributing/new_api_provider.html) to walk-through how to add a new API provider.
|
||||
|
||||
### Llama Stack Client SDKs
|
||||
|
||||
| **Language** | **Client SDK** | **Package** |
|
||||
| :----: | :----: | :----: |
|
||||
| Python | [llama-stack-client-python](https://github.com/meta-llama/llama-stack-client-python) | [](https://pypi.org/project/llama_stack_client/)
|
||||
| Swift | [llama-stack-client-swift](https://github.com/meta-llama/llama-stack-client-swift) | [](https://swiftpackageindex.com/meta-llama/llama-stack-client-swift)
|
||||
| Typescript | [llama-stack-client-typescript](https://github.com/meta-llama/llama-stack-client-typescript) | [](https://npmjs.org/package/llama-stack-client)
|
||||
| Kotlin | [llama-stack-client-kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) | [](https://central.sonatype.com/artifact/com.llama.llamastack/llama-stack-client-kotlin)
|
||||
|
||||
Check out our client SDKs for connecting to a Llama Stack server in your preferred language, you can choose from [python](https://github.com/meta-llama/llama-stack-client-python), [typescript](https://github.com/meta-llama/llama-stack-client-typescript), [swift](https://github.com/meta-llama/llama-stack-client-swift), and [kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) programming languages to quickly build your applications.
|
||||
|
||||
You can find more example scripts with client SDKs to talk with the Llama Stack server in our [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) repo.
|
||||
|
||||
|
||||
## 🌟 GitHub Star History
|
||||
## Star History
|
||||
|
||||
[](https://www.star-history.com/#meta-llama/llama-stack&Date)
|
||||
|
||||
## ✨ Contributors
|
||||
|
||||
Thanks to all of our amazing contributors!
|
||||
|
||||
<a href="https://github.com/meta-llama/llama-stack/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=meta-llama/llama-stack" />
|
||||
</a>
|
||||
6
docs/static/imported-files/usage.json
vendored
6
docs/static/imported-files/usage.json
vendored
|
|
@ -1,6 +0,0 @@
|
|||
{
|
||||
"files": [
|
||||
"docs/getting_started/demo_script.py",
|
||||
"README.md"
|
||||
]
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue